Deep learning radio-clinical signatures for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients.

Journal: International journal of surgery (London, England)
PMID:

Abstract

BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatures from pretreatment oversampled computed tomography (CT) images to predict the response to NCT and prognosis of LAGC patients.

Authors

  • Can Hu
    Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
  • Wujie Chen
    Department of Radiology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institutes of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou.
  • Feng Li
    Department of General Surgery, Shanghai Traditional Chinese Medicine (TCM)-INTEGRATED Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
  • Yanqiang Zhang
    Industrial Research Institute of Robotics and Intelligent Equipment, Harbin Institute of Technology, Weihai 264209, China. 15732031132@163.com.
  • Pengfei Yu
    Xijing Hospital, Fourth Military Medical University, Xi'an, China.
  • Litao Yang
    Department of Surgery, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310000, Zhejiang, China.
  • Ling Huang
    School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, 510640, China.
  • Jiancheng Sun
    Department of Gastrointestinal Surgery, The Affiliated Hospital of Wenzhou Medical University, Wenzhou.
  • Shangqi Chen
    Department of General Surgery, HwaMei Hospital, University of Chinese Academy of Sciences, Ningbo.
  • Chengwei Shi
    Department of Gastrointestinal Surgery, The Affiliated Hospital of Zhejiang Chinese Medical University.
  • Yuanshui Sun
    Department of Gastrointestinal Surgery, Tongde Hospital of Zhejiang Province.
  • Zaisheng Ye
    Department of Gastrointestinal Surgical Oncology, Fujian Cancer Hospital and Fujian Medical University Cancer Hospital, Fuzhou, 350000, China.
  • Li Yuan
    Research Institute of Natural Gas Technology, Petro China Southwest Oil and Gas Field Company, Chengdu, 610213, China.
  • Jiahui Chen
    Molecular Analytics and Photonics (MAP) Lab, Program of Polymer and Color Chemistry, Department of Textile Engineering, Chemistry and Science, North Carolina State University, 1020 Main Campus Drive, Raleigh, NC, 27606, USA.
  • Qin Wei
    Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China. Electronic address: sdjndxwq@163.com.
  • Jingli Xu
    Department of Gastric Surgery.
  • Handong Xu
    Department of Gastric Surgery.
  • Yahan Tong
    Department of Radiology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institutes of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou.
  • Zhehan Bao
    Department of Gastric Surgery.
  • Chencui Huang
    Department of Research Collaboration, R&D Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing, China.
  • Yiming Li
    Department of Cardiology, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Yian Du
    Department of Gastric Surgery.
  • Zhiyuan Xu
    Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, 13210.
  • Xiangdong Cheng
    Department of Gastric Surgery.